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Modelling the Economic Impact of Climate Change: Early Results, Methodological Challenges Roberto Roson Università Ca’Foscari, ICTP and FEEM EEE Seminar , Trieste, December 16th, 2003. Motivation. To provide a basic overview of the methodology
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Modelling the Economic Impact of Climate Change: Early Results, Methodological Challenges Roberto Roson Università Ca’Foscari, ICTP and FEEM EEE Seminar , Trieste, December 16th, 2003
Motivation • To provide a basic overview of the methodology • To illustrate and comment some early simulation results
Integrated Assessment Models Myth and Reality
An Ideal IAM Physical Effects Socio-Economic System(s) Climate System(s) Emissions
Actual Approach #1: IPCC • A series of socio-economic “scenarios” (A1, A2, B1, B2) • Forecasts of future climate consistent with given benchmarks • No feedback on the economy
Actual Approach #2: RICE • A series of parallel regional growth model linked by the climate externality • Emissions proportional to GDP • Climate module translates emissions into temperature changes • Temperature affects productivity (potential GDP)
Inadequacy of Current IAM Models • the description of the world economic structure is often too simplistic: limited number of industries (sometimes only one good, available for both consumption and investment), poor or absent description of international trade and capital flows. • the multi-dimensional nature of the impact of the climate change on the economic systems is disregarded. This is usually accommodated by specific ad-hoc relationships, making a certain fraction of potential income “melting away” as temperature increases
The General Equilibrium Concept p S(p,…) D(p,…) q
Simulation #1: Sea Level Rise • Two scenarios: no protection/ full protection • NP: reduction in the land stock • FP: additional protective investment expenditure
Simulation #2: Health • Two simultaneous effects • Variations in labour stock/productivity • Exogenous change in health services expenditure (by the public sector)
Simulation #3: Tourism • Estimation of O/D matrices of tourists with and without climate change • Hypothesis: % change in the number of tourists in a region = % change of tourism expenditure • Apply exogenous variations in the consumption demand of (1) recreational services and (2) hotels and restaurants within the broader sector “Trade”